class_docstr: Task for training masked language models (e.g., BERT, RoBERTa).
class_docstr_tok: ["Task","for","training","masked","language","models","(","e.g.",",","BERT",",","RoBERTa",")","."]
code: def setup_task(cls, args, **kwargs):
      paths = utils.split_paths(args.data)
      assert len(paths) > 0
      dictionary = Dictionary.load(os.path.join(paths[0], "dict.txt"))
      logger.info("dictionary: {} types".format(len(dictionary)))
      return cls(args, dictionary)
  
file_path: fairseq/fairseq/tasks/multilingual_masked_lm.py
imports: import logging
  import os
  import numpy
  import torch
  from fairseq import utils
  from fairseq.data import ConcatDataset, Dictionary, IdDataset, MaskTokensDataset, NestedDictionaryDataset, NumelDataset, NumSamplesDataset, PadDataset, PrependTokenDataset, RawLabelDataset, ResamplingDataset, SortDataset, TokenBlockDataset, data_utils, encoders
  from fairseq.tasks import LegacyFairseqTask, register_task
label_desc: Use image node_id 3 for calling the MultiLingualMaskedLMTask obj's underlying member method code with example usage: obj.setup_task(cls, args) and returns: cls